Gaussian KD-trees for fast high-dimensional filtering
ACM SIGGRAPH 2009 papers
PatchMatch: a randomized correspondence algorithm for structural image editing
ACM SIGGRAPH 2009 papers
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
Bregman vantage point trees for efficient nearest neighbor queries
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Nearest-neighbor search algorithms on non-Euclidean manifolds for computer vision applications
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
The generalized patchmatch correspondence algorithm
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Lost in binarization: query-adaptive ranking for similar image search with compact codes
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
The PatchMatch randomized matching algorithm for image manipulation
Communications of the ACM
Random forest for image annotation
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Mixed-resolution patch-matching
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Local label descriptor for example based semantic image labeling
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
TreeCANN - k-d tree coherence approximate nearest neighbor algorithm
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Transfer of albedo and local depth variation to photo-textures
Proceedings of the 9th European Conference on Visual Media Production
Feature match: an efficient low dimensional PatchMatch technique
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Spatially aware patch-based segmentation (SAPS): an alternative patch-based segmentation framework
MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
Dual local consistency hashing with discriminative projections selection
Signal Processing
Special Section on CAD/Graphics 2013: Image compositing using dominant patch transformations
Computers and Graphics
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Many computer vision algorithms require searching a set of images for similar patches, which is a very expensive operation. In this work, we compare and evaluate a number of nearest neighbors algorithms for speeding up this task. Since image patches follow very different distributions from the uniform and Gaussian distributions that are typically used to evaluate nearest neighbors methods, we determine the method with the best performance via extensive experimentation on real images. Furthermore, we take advantage of the inherent structure and properties of images to achieve highly efficient implementations of these algorithms. Our results indicate that vantage point trees, which are not well known in the vision community, generally offer the best performance.